print("Loading movie ratings...")
data = source.loadMovieLensRating()
print("Prepare movie information...")
source.computeMovieInformation()
print("Creating ranking for each movie ...")
rankings = source.getPopularityRanksByRating()
return (source, data, rankings)
np.random.seed(0)
random.seed(0)
# Load up common data set for the recommender algorithms
(dataSource, data, rankings) = LoadData()
# Construct an Evaluator to, you know, evaluate them
evaluator = Evaluator(data, rankings)
contentKNN = KNNAlgorithm()
evaluator.AddAlgorithm(contentKNN, "ContentKNN")
# Just make random recommendations
# Random = NormalPredictor()
# evaluator.AddAlgorithm(Random, "Random")
evaluator.Evaluate()
useTargetId = 85
totalMovieNeeded = 5
evaluator.GetRecomendationMovie(dataSource, useTargetId, totalMovieNeeded)
